Optimal placement of precast bridge deck slabs with respect to precast girders using 3D laser scanning

Yoon, Seongheum; Wang, Qian; Sohn, Hoon

doi:10.1016/j.autcon.2017.11.004

Cited by 41 publications

(12 citation statements)

References 28 publications

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“…DQA Based on Laser Scanning. Numerous studies have suggested employing DQA through the utilization of laser scanning on building elements, including steel-frame structures [25,26], building facades [27,28], timber beams [29], and precast bridge slabs [30]. For example, Bosche et al [25,26] proposed an object detection method that recognizes construction components from point cloud data for dimensional compliance inspection of a steel-frame structure.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The validation tests on timber beams provided a relative dimensional error of 3%. Yoon et al [30] also presented an optimal placement method for assembling precast bridge slabs based on laserscanner data. The as-built dimensions of dimensional features on the girders were first extracted to guide the placement of the precast deck panels.…”

Section: Literature Reviewmentioning

confidence: 99%

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A Comparison Study of Edge Line Estimation Algorithms for Dimensional Quality Assessment of Precast Concrete Slabs

Yi,

Li,

Thedja

et al. 2024

Advances in Civil Engineering

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Point cloud data-based edge line extraction is an important task for accurate geometrical inspection of precast concrete (PC) elements in the construction industry. Although a few edge extraction algorithms have been developed so far based on point cloud data, little attention has been paid on which edge extraction algorithm performs the best in terms of edge estimation accuracy. To tackle the research gap, this study aims to evaluate currently available edge extraction algorithms in order to determine optimal algorithm for precise geometrical inspection of PC elements. To do this, simulated scan points are first generated and used for algorithm performance analysis using a geometrical model and a measurement noise modeling that determine the coordinates of simulated scan points. For validation of the simulation approach, comparison tests with experimental data are performed and the results show that the simulation approach has a high similarity of more than 90% compared to experimental data in terms of the number of scan points, scan pattern, and scan density, proving the effectiveness of the simulation-based evaluation method. In addition, it shows that a least square regression (LSR) algorithm provides the best performance with an edge extraction accuracy of 1.56 and 2.71 mm for simulated and experimental scan points, respectively. The contributions of this study are (1) development of the geometrical model and noise modeling based on actual scan data and (2) validation of simulated-based evaluation method on the lab-scale PC slabs.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A Comparison Study of Edge Line Estimation Algorithms for Dimensional Quality Assessment of Precast Concrete Slabs

Yi,

Li,

Thedja

et al. 2024

Advances in Civil Engineering

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“…Currently, 3D point clouds have been successfully applied to various dimensional quality inspections in infrastructure projects. In the field of precast components, a technique was presented to detect slab sizes and shear pocket sizes and positions to ensure the quality of precast concrete slabs [6]; and a framework was developed to examine slab sizes, girder sizes, shear pocket sizes and positions, and shear connector orientations and positions to guarantee the proper connection between precast bridge deck slabs and precast girders [7]. Since irregular precast components and precast components with holes increase the complexity of detection, a technique was presented to determine the panel depth, shear key sizes and positions, and flat duct positions of a precast bridge deck slab with geometric irregularities [8]; and a method was proposed to estimate panel sizes and squareness and hole sizes and positions for accelerating the measurement of precast concrete panels with holes [9].…”

Section: Introductionmentioning

confidence: 99%

Measuring The Spacing of Formwork System Members Using 3D Point Clouds

Wu¹,

Prieto²,

Soto³

2022

Proceedings of the Creative Construction E-Conference 2022

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Formwork systems significantly impact the safety risk, construction productivity, and capital investment of infrastructure projects. Ensuring that formwork systems are properly installed is fundamental to avoid those adverse impacts. To do that, quality inspection during installation is important. The traditional spacing inspection process of different members of the formwork system is time-consuming and labordemanding, and it is easily affected by the inspector's knowledge and skills. This study proposes a methodology for the spacing measurement of formwork system members using 3D point clouds to overcome these shortcomings. The feasibility and effectiveness of the proposed methodology were tested on a formwork system mockup. The mean absolute percentage error (MAPE) of the eight spacing measurements compared to those using a measuring tape was 1.05%. The experimental test demonstrates that the 3D point cloud approach is promising, and it has the potential to be an alternative solution to measure the spacing of formwork system members.

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“…In another common application, the laser scanners were used for tracking changes, mostly during construction, by comparing successive scans that are recorded throughout the process was studied 11,12 . Several methodologies have also been developed to locate objects in the as‐built geometry based on the BIMs of the as‐designed geometry 13,14 . Tracking of components within a point cloud during construction has been investigated in Bosche and Haas, 15 Chi et al, 16 and Sharif et al 17 Modeled and the as‐is conditions of the structure are compared to identify potential errors in the model 18 .…”

Section: Introductionmentioning

confidence: 99%

Using extracted member properties for laser‐based surface damage detection and quantification

Erkal

Hajjar

2020

Struct Control Health Monit

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Many existing structures suffer from damage due to age or accumulated damage from hazards. It is important to accurately assess the present conditions of these aging, deteriorating, and damaged structures. In recent years, laser scanners have been increasingly used for capturing the in situ conditions of structures. They are used for collecting dense and high-resolution point clouds of scenes for structural engineering applications. However, automatically extracting meaningful information from the point clouds remains a challenge, and the current state-of-the-art requires significant user interaction. In this work, a process for automatically extracting information from laser datasets such as the location, orientation, and size of objects in a scanned region, and location of damaged regions on a structure is established. First, widely accepted point cloud processing steps are used to divide the collected laser scanner data into meaningful point clusters. A new graph-based object detection algorithm is then used to generate skeletons of the extracted point clusters in order to detect structural members by using a model library consisting of common structural shapes. The obtained member information is then used for developing a new graph-based damage detection method, which compares the fitted object model with the as-is point cloud of the investigated object for locating defects, detecting alignment issues and points of discontinuity, computing changes in the cross-section through area calculation, and determining the total volume change on the investigated member. The effectiveness of the developed graph-based object and damage detection algorithms are tested and validated on test specimens and test-bed bridges.

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Optimal placement of precast bridge deck slabs with respect to precast girders using 3D laser scanning

Cited by 41 publications

References 28 publications

A Comparison Study of Edge Line Estimation Algorithms for Dimensional Quality Assessment of Precast Concrete Slabs

A Comparison Study of Edge Line Estimation Algorithms for Dimensional Quality Assessment of Precast Concrete Slabs

Measuring The Spacing of Formwork System Members Using 3D Point Clouds

Using extracted member properties for laser‐based surface damage detection and quantification

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